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Record W2159052107 · doi:10.1109/eicccc.2006.277214

Environmental Assessment of the Integration of Amine-based CO2 Capture Unit to Coal-Fired Power Plants for Greenhouse Gas Mitigation

2006· article· en· W2159052107 on OpenAlexaffabout
Bhurisa Thitakamol, Amornvadee Veawab, Adisorn Aroonwilas

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEngineering
TopicCarbon Dioxide Capture Technologies
Canadian institutionsUniversity of Regina
Fundersnot available
KeywordsFlue gasGreenhouse gasCoalAir pollutantsPower stationEnvironmental scienceWaste managementChemistryEngineeringAir pollutionElectrical engineeringOrganic chemistryEcology

Abstract

fetched live from OpenAlex

Coal-fired power plants produce flue gas containing a number of air pollutants including carbon dioxide (CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> ), a major greenhouse gas contributing to climate change. Capture of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> from the flue gas at the coal-fired power plants is one of the strategies to help Canada reduce its CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emissions, achieve its Kyoto protocol reduction target, and also ensure the continuation of fossil fuel utilization. This paper assessed potential environmental impacts of the amine-based CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> capture unit which is integrated to the coal-fired power plants for post-combustion treatment of flue gas. The assessment was performed by identifying pollutants and their emission sources, reviewing the toxicology, potential implications to the human health and the environment, as well as related environmental laws, and ultimately providing recommendations of means to minimize such impacts. The analysis shows that while installing a CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> capture unit leads to an environmental benefit through a reduction of CO <sub xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">2</sub> emission in the atmosphere, it may create unintentional and potential burdens to the human health and the environment through four pathways including treated gas, process wastes, fugitive emissions, and accidental emissions. Such burdens nevertheless can be predetermined and properly mitigated through a well-established environmental management program and mitigation measures.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: Bench or experimental
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.088
Threshold uncertainty score0.375

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.008
GPT teacher head0.215
Teacher spread0.207 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designBench or experimental
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations6
Published2006
Admission routes2
Has abstractyes

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